Fine-Scale Mapping of Particulate Matter Using Landsat Imagery and Low-Cost Sensor Data from Purpleair: A Case Study of Los Angeles
Author:
Affiliation:
1. University of Southern California,Spatial Sciences Institute, Dornsife College of Letters, Arts and Sciences,Los Angeles,CA,USA
Funder
Southern California Environmental Health Sciences Center
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10640349/10640352/10642252.pdf?arnumber=10642252
Reference21 articles.
1. Clearing the Air: A Review of the Effects of Particulate Matter Air Pollution on Human Health
2. Predicting PM2.5 atmospheric air pollution using deep learning with meteorological data and ground-based observations and remote-sensing satellite big data
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4. A land use regression model for predicting ambient fine particulate matter across Los Angeles, CA
5. Using a land use regression model with machine learning to estimate ground level PM2.5
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